Prabhat K. C.

According to our database, Prabhat K. C. authored at least 6 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Report on the AAPM Grand Challenge on deep generative modeling for learning medical image statistics.

Rucha Deshpande, Varun A. Kelkar, Dimitrios S. Gotsis, Prabhat K. C., Rongping Zeng, Kyle J. Myers, Frank J. Brooks, Mark A. Anastasio

CoRR, 2024

2023

Assessing the Ability of Generative Adversarial Networks to Learn Canonical Medical Image Statistics.

Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Prabhat K. C., Kyle J. Myers, Rongping Zeng, Mark A. Anastasio

IEEE Trans. Medical Imaging, June, 2023

Evaluating generative stochastic image models using task-based image quality measures.

Varun A. Kelkar, Dimitrios S. Gotsis, Rucha Deshpande, Frank J. Brooks, Prabhat K. C., Kyle J. Myers, Rongping Zeng, Mark A. Anastasio

Proceedings of the Medical Imaging 2023: Image Perception, 2023

2022

Evaluating procedures for establishing generative adversarial network-based stochastic image models in medical imaging.

Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Kyle J. Myers, Prabhat K. C., Rongping Zeng, Mark A. Anastasio

Proceedings of the Medical Imaging 2022: Image Perception, 2022

2021

Deep neural networks-based denoising models for CT imaging and their efficacy.

Prabhat K. C., Rongping Zeng, M. Mehdi Farhangi, Kyle J. Myers

CoRR, 2021

2018

Model-Based Iterative Reconstruction of Magnetization Using Vector Field Electron Tomography.

K. Aditya Mohan, Prabhat K. C., Charudatta Phatak, Marc De Graef, Charles A. Bouman

IEEE Trans. Computational Imaging, 2018